Stock Market Sector Research Articles

تأثيــر الإفصاح المحاسبي عن معلومات جائحة فيـروس کورونا على القيمة السوقية للأسهم بالبورصة المصرية: منهجية دراسة الحدث

- هدف الدراسة: تمثل الهدف الرئيس للدراسة في عرض وتحليل الآثار الحالية والمحتملة لتداعيات جائحة فيروس کورونا المستجد (COVID-19) ببيئة التقارير المالية، وبيان محددات الإفصاح المحاسبي عن معلومات الجائحة في ضوء متطلبات معايير المحاسبة الدولية والمصرية والإصدارات والممارسات المهنية ذات الصلة، وتحديد أهم المشاکل والتحديات التي تعوق هذا الإفصاح وآليات مواجهتها. فضلا عن قياس أثر محددات الإفصاح المحاسبي على القيمة السوقية للأسهم بالبورصة المصرية. - التصميم والمنهجية: قام الباحث بإجراء مسح ميداني لبيان محددات الإفصاح المحاسبي عن جائحة فيروس کورونا وذلک لثلاثة فئات تضم معدي التقارير المالية، والمستثمرين بالبورصة، والأکاديميين بأقسام المحاسبة والمراجعة، وتم تحليل إجابات عينات الدراسة بواقع 153مفردة بنسبة 85% باستخدام أساليب برنامج التحليل الإحصائي SPSS. کما قام الباحث بإجراء دراسة تطبيقية لعدد 214 شرکة مقيده بالبورصة المصرية من خلال تحليل سلسلة زمنية يومية بلغت 243 يوم تداول عن عام 2020م بإستخدام منهجية تحليل الحدث، لقياس أثر الإفصاح عن معلومات الجائحة على القيمة السوقية للأسهم. - النتائج: کشفت نتائج المسح الميداني عن عدم وجود تمايز ذو دلالة معنوية بين فئات الدراسة بشأن محددات الإفصاح المحاسبي عن معلومات جائحة کورونا، في حين يوجد تمايز ذو دلالة معنوية بين فئات الدراسة بشأن مشاکل وتحديات الإفصاح المحاسبي عن معلومات جائحة کورونا والآليات المقترحة للتغلب عليها. کما کشفت الدراسة التطبيقية عن وجود تأثير ذو دلالة معنوية بين الإفصاح عن معلومات جائحة فيروس کورونا المستجد والقيمة السوقية لأسهم الشرکات المقيدة بالبورصة المصرية، وکذلک وجود تمايز ذو دلالة معنوية بين قطاعات سوق الأوراق المالية المصرية (18 قطاع) من حيث تأثر القيمة السوقية للسهم بتداعيات جائحة فيروس کورونا، وذلک باستخدام معدل العائد غير الطبيعي التراکمي CAR للأسهم. - الأصالة والإضافة: تسهم هذه الدراسة في بيان محددات الإفصاح المحاسبي عن معلومات جائحة فيـروس کورونا وقياس أثرها على القيمة السوقية للأسهم بالبورصة المصرية، من خلال إستخدام منهجية دراسة الحدث. Abstract: - Study objective: The main objective of the study was to present and analyze the current and potential impacts of the repercussions of the emerging corona virus (COVID-19) pandemic in the financial reporting environment, and to clarify the determinants of accounting disclosure of pandemic information in light of the requirements of international and Egyptian accounting standards, publications and relevant professional practices, and to identify the most important problems and challenges that hinder this disclosure and the mechanisms to confront them. As well as measuring the impact of accounting disclosure determinants on the market value of shares on the Egyptian Stock Exchange. - Design and methodology: The researcher conducted a field survey to clarify the determinants of accounting disclosure about Coronavirus pandemic for three categories, accountants, stock exchange investors, and academics in accounting and auditing departments. The researcher also conducted an applied study for 214 companies listed on (E.S.E) by analyzing a daily time series of 243 days for the year 2020, using the event analysis methodology, to measure the impact of disclosure of pandemic information on the market value of shares. - The study results: The results of the field survey revealed that there is no significant discriminants between the study categories regarding the determinants of the accounting disclosure of the Corona pandemic information, while there is a significant discriminants between the study groups regarding the problems and challenges of the accounting disclosure of the COVID-19 information and the proposed mechanisms to overcome them. The applied study also revealed that there is a significant impact between the disclosure of information about the emerging Coronavirus pandemic and the market value of the shares of companies listed on (E.S.E), as well as the existence of a significant discriminants between the Egyptian stock market sectors (18 sectors) in terms of the market value of the share affected by the repercussions of the pandemic Coronavirus, using the CAR. - Originality and addition: This study contributes to clarifying the determinants of the accounting disclosure of the Corona virus pandemic information and measuring its impact on the market value of stocks on (E.S.E), by using the event methodology analysis.

Forecasting sector stock market returns

We seek to forecast sector stock returns using established predictor variables. Existing empirical evidence focuses on market level data, and thus, sector data provide fertile ground for research. In addition to in-sample predictive regressions, we consider recursive and rolling forecasts and whether such forecasts can be used successfully in a sector rotation portfolio. The results for ten sectors and eleven predictor variables highlight that two variables, the default return and stock return variance, have significant predictive power across the stock market series. Forecast results are also supportive of these series (especially the default return), which can outperform benchmark and alternative forecast models across a range of metrics. A sector rotation strategy based on these forecasts produces positive abnormal returns and a Sharpe ratio higher than the baseline model. An examination of the sectors at each rotation reveals that a small number of dominate in the constructed portfolios.

Shades between Black and Green Investment: Balance or Imbalance?

This paper analyses the links established between environmental indices and the oil price adopting a double perspective, long-term and short-term relationships. For that purpose, we employ the Bounds Test and bivariate conditional heteroscedasticity models. In the long run, the pattern of behaviour of environmental indices clearly differed from that of the oil prices, and it was not possible to identify cointegrating vectors. In the short-term, it was possible to conclude that, in contemporaneous terms, the variables studied tended to follow similar paths. When the lag of the oil price variable was considered, the impacts produced on the stock market sectors were partially of a negative nature, which allows us to suppose that this variable plays the role of a risk factor for environmental investment.

The Australian Stock Market’s Reaction to the First Wave of the COVID-19 Pandemic and Black Summer Bushfires: A Sectoral Analysis

In this study, we investigated the impact of the first wave of the COVID-19 pandemic on various sectors of the Australian stock market. Market capitalization and equally weighted indices were formed for eleven Australian sectors to examine the influence of the pandemic on them. First, we examined the financial contagion between the Chinese stock market and Australian sector indices through the dynamic conditional correlation fractionally integrated generalized autoregressive conditional heteroskedasticity (DCC-FIGARCH) model. We found high time-varying correlations between the Chinese stock market and most of the Australian sector indices, with the financial, health care, information technology, and utility sectors displaying a decrease in co-movements during the pandemic. The Modified Iterative Cumulative Sum of Squares (MICSS) analysis results indicated the presence of structural breaks in the volatilities of most of the sector indices around the end of February 2020, but consumer staples, industry, information technology and real estate indices did not display any break. Markov regime-switching regression analysis depicted that the pandemic has mainly affected three sectors: consumer staples, industry, and real estate. When we considered the firm size, we found that smaller companies in the energy sector exhibited gradual deterioration, whereas small firms in the consumer staples sector experienced the largest positive impact from the pandemic.

Asymmetric volatility spillover among Chinese sectors during COVID-19

Inter-sectoral volatility linkages in the Chinese stock market are understudied, especially asymmetries in realized volatility connectedness, accounting for the catastrophic event associated with the COVID-19 outbreak. In this paper, we examine the asymmetric volatility spillover among Chinese stock market sectors during the COVID-19 pandemic using 1-min data from January 2, 2019 to September 30, 2020. In doing so, we build networks of generalized forecast error variances by decomposition of a vector autoregressive model, controlling for overall market movements. Our results show evidence of the asymmetric impact of good and bad volatilities, which are found to be time-varying and substantially intense during the COVID-19 period. Notably, bad volatility spillover shocks dominate good volatility spillover shocks. The findings are useful for Chinese investors and portfolio managers constructing risk hedging portfolios across sectors and for Chinese policymakers monitoring and crafting stimulating policies for the stock market at the sectoral level.

Sectoral Nonlinear Causality Between Stock Market Volatility and the COVID-19 Pandemic: Evidence From India

This paper examines the linear and nonlinear relationship between daily confirmed COVID-19 cases and sectoral stock market volatility in India. The linear Granger causality test reveals bidirectional causality. Further, we observe that bidirectional nonlinear Granger causality exists between stock market volatility and COVID-19. This implies that the historical and lagged information can have a significant role in predicting COVID-19 cases and the stock market.

Impact of the COVID-19 outbreak on the US equity sectors: Evidence from quantile return spillovers

The aim of this study is to examine the extreme return spillovers among the US stock market sectors in the light of the COVID-19 outbreak. To this end, we extend the now-traditional Diebold-Yilmaz spillover index to the quantiles domain by building networks of generalized forecast error variance decomposition of a quantile vector autoregressive model specifically for extreme returns. Notably, we control for common movements by using the overall stock market index as a common factor for all sectors and uncover the effect of the COVID-19 outbreak on the dynamics of the network. The results show that the network structure and spillovers differ considerably with respect to the market state. During stable times, the network shows a nice sectoral clustering structure which, however, changes dramatically for both adverse and beneficial market conditions constituting a highly connected network structure. The pandemic period itself shows an interesting restructuring of the network as the dominant clusters become more tightly connected while the rest of the network remains well separated. The sectoral topology thus has not collapsed into a unified market during the pandemic.

Macroeconomic Variables and Sector-Specific Returns: Evidence from Turkish Stock Exchange Market

This study investigates the impact of macroeconomic variable shocks on industrial and financial stock returns in the Borsa Istanbul. To this end, we use the generalized forecast error variance decompositions and generalized impulse responses. The results show that inflation, the growth rate of the money supply, and the exchange rate provide significant information for forecasting industrial and financial stock market volatility. The impact of industrial production on stock returns appears to be negligible, both in the short and long horizons. The study extends our understanding of sectoral stock market behavior in a developing country.

Anticipated Volatility, Unanticipated Volatility Shocks, Excess Monthly Returns and Stock Market Behaviour of Pakistan

An investor considers various factors to choose the financial assets. The portfolio theory suggests that risk, return, taxes, information and liquidity are vital factors in portfolio choice. The study is based on risk premium, uncertainty, shocks and volatility of Pakistan stock exchange market. The study has used monthly time series data of returns of ten sectors of Pakistan stock market ranging from 2006 to 2014 to measure the anticipated and unanticipated factors of risk, return and uncertainty. Using CAPM, it is pointed out that volatility factor is present and high in overall stock market and the level of volatility in different sectors of the market moves in the same direction which suggest that speculative activities are widely spread in every sector and in overall market as well.

Policy uncertainty and sectoral stock market volatility in China

This study examines the dynamic volatility connectedness between different types of policy uncertainty and sectoral stock markets in both the time and frequency domains in China. Using the time–frequency connectedness index approach, we find extremely high connectedness between policy uncertainty and Chinese sectoral stock markets mainly in the medium and long terms. In particular, uncertainty regarding monetary policies makes the weakest contribution to spillovers among the four policy uncertainties, while uncertainty regarding trade policies contributes prominently. The energy, financial, IT, telecommunication services and utilities sectors are the most vulnerable to policy uncertainties.

PENGARUH COVID-19 TERHADAP HARGA SAHAM DI INDONESIA TAHUN 2019-2020

Saham adalah salah satu instrumen pasar modal yang dapat didefiniskan sebagai tanda penyertaan modal seorang atau sepihak (badan usaha) dalam suatu perusahaan atau perseroan terbatas. Faktor yang terjadi sekarang dalam sektor pasar saham yaitu adanya dampak dari virus corona terhadap indeks harga saham dan arus dana asing ke pasar saham. Maka sangat perlu untuk dilakukan analisis pengaruh dampak virus pandemi corona terhadap sektor pasar saham untuk melihat bagaimana perbandingan pergerakan IHSG di Indonesia sebelum terjadi pandemi dan pada saat terjadi pandemi Covid-19. Metode yang digunakan untuk analisis perbandingan adalah Simple Moving Average dan Weighted Moving Average. Dari hasil analisis deskriptif pada data IHSG di Indonesia didapatkan rata-rata pada variabel Adj Close sebelum terjadi pandemi adalah sebesar 6353.71, dengan nilai minimum sebesar 5907.12 dan nilai maksimum sebesar 6525.36. Nilai rata-rata pada saat terjadi pandemi adalah sebesar 5143.929, dengan nilai minimum sebesar 3937.632 dan nilai maksimum sebesar 6325.406. Hasil perbandingan menunjukkan metode Weighted Moving Average digunakan karena dengan nilai MAPE IHSG 2019 sebesar 0.844287 nilai MAPE IHSG 2020 sebesar 3.489167 yang lebih kecil dari metode Simple Moving Average. Serta hasil dari perbandingan dampak IHSG dari sebelum terjadi pandemi dengan data dimana sedang terjadi pandemi sangat berpengaruh dan IHSG menurun saat dinyatakan Indonesia sudah terinfeksi Covid-19.

COVID-19 Pandemic Economic Crisis in Sri Lanka

A worldwide emergency has been proclaimed by the World Health Organization because of the global spread of COVID-19. The study examines the consequences of the pandemic on GDP, employment, inflation, stock market, and external sector performance in Sri Lanka, as well as poverty. COVID-19 news reports, as well as data gathered and analyzed from national and international research initiatives, were the foundation of the paper's content, as were news articles about COVID-19. COVID-19 has created direct or indirect economic disruptions in Sri Lanka in the short to medium term. As a result of these pandemics occurring over time, COVID-19 and its impact on the Sri Lankan economy have been emphasized in this article. Major income-producing businesses have been hit by the COVID-19 pandemic in several ways. It shows that all types of poverty have a greater chance of increasing in occurrence.

Herding behaviour in Turkish stock market sector indices: the effect of COVID-19 outbreak

Herding behaviour in Turkish stock market sector indices: the effect of COVID-19 outbreak

The Impact of the Muslim Boycott to Protest Against The Caricatures Of The Prophet Muhammad (PBUH) On The French Stock Market Sectors

The Impact of the Muslim Boycott to Protest Against The Caricatures Of The Prophet Muhammad (PBUH) On The French Stock Market Sectors

The Impact of Brexit on the United Kingdom Stock Market Sectors in Under of the COVID-19 Crisis

This study aims to analyze the impact of Brexit on In Light Of the COVID- 19 Crisis on the returns of the sectoral indices of the United Kingdom Stock Exchange. For this purpose, total of (30) sectoral indicators were included in the study.The study data consists of the daily closing prices of 30 indicators for the United Kingdom market sectors, from the beginning of the Brexit time 02/01/2019 to 02/01/2021. Results provide Regarding abnormal returns, the significance of variation among (ARs) is shown between Pre-Brexit and Post-Brexit for abnormal returns. Also, a robustness check using cumulative abnormal returns (CARs) supports this result. And accordingly, there are differences between the returns of the UK market sectors indices before and after Brexit. this is in favor of abnormal returns and abnormal cumulative returns for sectoral indices pre-Brexit.results provide that indicators of market sectors have reacted to Coronavirus spread, the results indicate that the sectors' normal returns appear to be more sensitive to new Coronavirus Deaths (RCCD) than New Coronavirus Cases (RNCC),the sectors that reacted negatively (24) sectors, the sectors that interacted positively (6) sectors, according to comparing the averages of abnormal return before and after Brexit during the study period.

A Bibliometric Review of Stock Market Prediction: Perspective of Emerging Markets

Abstract The objective of the paper is to identify predictive models in stock market prediction focusing on a scenario of the emerging markets. An exploratory analysis and conceptual modelling based on the extant literature during 1933 to 2020 have been used in the study. The databases of Web of Science, Scopus, and JSTOR ensure the reliability of the literature. Bibliometrics and scientometric techniques have been applied to the retrieved articles to create a conceptual framework by mapping interlinks and limitations in past studies. Focus of research is hybrid models that integrate big data, social media, and real-time streaming data. Key finding is that actual phenomena affecting stock market sectors are diverse and, hence, limited in generalization. The future research must focus on models empirically validated within the emerging markets. Such an approach will offer an insight to analysts and researchers, policymakers or regulators.

Geopolitical Risk and Tourism Stocks of Emerging Economies

A bulk of literature suggests that geopolitical events such as terrorist attacks dampen tourism demand. However, there is little research on whether this effect helps predict the return of the tourism equity sector. We provide country-level evidence on whether local and global geopolitical risk (GPR) predicts the first and second moments of tourism stocks in emerging economies. This objective was achieved by employing the non-parametric causality-in-quantiles (CiQ) model and a cross-quantilogram (CQ) test, which allowed us to uncover the predictive potential of GPR for the tourism sector equities. Our findings, obtained through the CiQ model, suggest that while both local and global GPRs carry significant potential for predicting the returns and volatility of tourism stocks of most emerging economies under normal market conditions, they seem to play no such role in certain countries. These countries include South Korea, for which only a limited number of tourism stocks trade on the domestic stock market compared to other sectors, and Colombia, for which both the domestic stock market and tourism sectors are at an emerging stage. Further, it turns out that, compared to its local counterpart, global GPR has a more pronounced predictive power for the tourism stocks of emerging economies. Finally, with some exceptions, the results are qualitatively similar, and hence reasonably robust, to those when a directional predictability model is applied. Given that geopolitical shocks are largely unanticipated, our findings underscore the importance of a robust tourism sector that can help the market recover to stability as well as an open economy that allows local investors to diversify country-specific risks in their portfolios. Implications and directions for future research are discussed.

The Unprecedented Australian Stock Market Reaction to the Black Summer Bushfires and the COVID-19 Pandemic Outbreak: A Sectoral Analysis

In this study, we investigated the impact of the first wave of the COVID-19 pandemic on various sectors of the Australian stock market. Market capitalization and equally weighted indices were formed for eleven Australian sectors to examine the influence of the pandemic on them. First, we examined the financial contagion between the Chinese stock market and Australian sector indices through the dynamic conditional correlation fractionally integrated generalized autoregressive conditional heteroskedasticity (DCC-FIGARCH) model. We found high time-varying correlations between the Chinese stock market and most of the Australian sector indices, with the financial, health care, information technology, and utility sectors displaying a decrease in co-movements during the pandemic. The Modified Iterative Cumulative Sum of Squares (MICSS) analysis results indicated the presence of structural breaks in the volatilities of most of the sector indices around the end of February 2020, but consumer staples, industry, information technology and real estate indices did not display any break. Markov regime-switching regression analysis depicted that the pandemic has mainly affected three sectors: consumer staples, industry, and real estate. When we considered the firm size, we found that smaller companies in the energy sector exhibited gradual deterioration, whereas small firms in the consumer staples sector experienced the largest positive impact from the pandemic.

Volatility Spillover Between Stock Market Sectors

In this study, volatility spillover and volatility relationship of Istanbul Stock Exchange (BIST) basic markets were investigated by using daily data between 4 January 2010 and 28 August 2019. Volatility spillover between industry, trade, service and financial sectors were examined by causality test in the variance Hafner and Herwartz (2006), and inter-sector relations were examined by DCC GARCH method. In this study, dynamic conditional correlation between BIST core markets and volatility spillover from industry, trade and service sector to financial sector were observed. In addition, it has been determined that the relationship between the major sectors of BIST varies with time and that economic and political events partially determine these changes. It has been understood that the relationship between financial-industry, service-trade, financial-service and service-industry sectors is higher than the relationship between trade-financial and industry-trade sectors. According to these results, it is not possible to reduce risk through diversification based on BIST core markets. The results provide guidance for investors, risk managers and portfolio managers.

COVID-19 and investor sentiment influence on the US and European countries sector returns

Although some studies recently address the association between COVID-19 sentiment and returns, volatility, or stock trading volume, no one conducts an analysis to measure the impact of investor rationality or irrationality on the influence on countries and sectors’ returns. This work creates a text media sentiment and combines its influence with the outbreak cases on the stock market sector returns of the US, Europe, and their main countries most affected by the pandemic. This allows us to perceive the ranking impact of rationality or irrationality on country and sector stock returns. This work applies a random-effects robust panel estimation, with an M-estimator. This paper concludes that US returns are more sensitive to sentiment, and thus more prone to irrational factors than confirmed cases compared to Europe and that country factors influence the returns differently. In Italy and Spain as the most punished countries in Europe apart from the UK, present sector indexes return more reactive to verified cases, or rationality, namely, tourism, real estate, and the automobile (this last one in Italy). The importance of this work resides in providing a new in-depth analysis of irrational behavioral metrics among countries, which allows for comparison. Moreover, it allows observing which sectors’ and which countries’ asset returns are most sensitive to rational or irrational expressions of events, allowing for arbitraging, financial planning for investors, decision-makers, and academia on an in and out of pandemic context. AcknowledgmentThis work is funded by National Funds through the FCT – Foundation for Science and Technology, I.P., within the scope of the project Refª UIDB/05583/2020. Furthermore, we would like to thank the Research Centre in Digital Services (CISeD) and the Polytechnic Institute of Viseu for their support.